Improved Particle Swarm Optimization for Economic Dispatch of Combined Heat and Power System

This paper proposes an improved particle swarm optimization with multiplier updating (IPSO-MU) to solve economic dispatch problems of combined heat and power (CHP) system. The improved particle swarm optimization (IPSO) has the ability to efficiently search and actively explore solutions. Multiplier updating (MU) is introduced to avoid deforming the augmented Lagrange function (ALF), which is adopted to manage system constraints of the CHP. The proposed IPSO-MU integrates the IPSO with the MU. Two CHP examples are employed to demonstrate that the proposed algorithm has the benefits of straightforwardness; ease of implementation; better effectiveness and efficiency than the particle swarm optimization (PSO); automatic adjustment of the randomly assigned penalty to an appropriate value, and the requirement for only a small population when applied to CHP operations.